Recently, smart wearables, typically as wearable ECG, EEG, blood pressure, pulse, respiration, sleep, and motion monitoring, have been gaining a significant role in the field of healthcare and are looking to be a big and promising market in the technology industry. They are scientifically and clinically useful for better monitoring of real-time, long-term, and dynamic physiological and pathological processes, hence providing opportunities for the development of new diagnostic and therapeutic techniques. These could be expedient for the management of chronic illnesses, such as cardiovascular disease, sleep disorder, emotional problem, cognitive impairment, and functional decline, as well as for the healthcare applications for special populations, like the aged, pregnant women, athletes, astronauts, and so on. The mainstream in smart wearables research is moving towards more sophisticated methodologies based on clinical “big data,” artificial intelligence, advanced signal processing, service robots, and network, as well as more robust signal acquisition approaches.

The purpose of this special issue is to publish high-quality research papers as well as review articles addressing recent technology advances in signal processing and device development for smart wearables, as well as the implementation of these technologies for clinical applications. Original, high quality contributions that are not yet published or that are not currently under review by other journals or peer-reviewed conferences are welcomed.

Potential topics include but are not limited to the following:

• Clinical wearable database and the corresponding annotations and analysis toolbox
• Signal quality assessment and control for dynamic wearable data
• Real-time human vital signs monitoring for the chronic illnesses
• Telemedicine, mobile health, and human sensor network techniques
• Flexible electrode, fabric electrode, and dry electrode for wearable devices
• Sensors for smart wearables: working principle and performance
• Low power and energy-efficient hardware for wearable devices
• Compressed sensing, nonlinear analysis, multimodal signal processing, machine learning, and artificial intelligence for wearable ECG, EEG, blood pressure, pulse, respiration, sleep, and motion signals
• High-performance computing and big data processing
• Intelligent health monitoring systems (including service robots) combining wearable technologies for health monitoring and disease diagnosis
• Clinical applications for chronic illnesses detection, including cardiac arrhythmia, hypertension, heart failure, sleep disorder, emotional problem, cognitive impairment, and functional decline